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Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method

Transcriptomic data of cultured cells treated with a chemical are widely recognized as useful numeric information that describes the effects of the chemical. This property is due to the high coverage and low arbitrariness of the transcriptomic data as profiles of chemicals. Considering the importanc...

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Autores principales: Ishiguro, Hiromu, Mizuno, Tadahaya, Uchida, Yasuo, Sato, Risa, Sasaki, Hayate, Nemoto, Shumpei, Terasaki, Tetsuya, Kusuhara, Hiroyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006730/
https://www.ncbi.nlm.nih.gov/pubmed/36915410
http://dx.doi.org/10.1093/nargab/lqad022
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author Ishiguro, Hiromu
Mizuno, Tadahaya
Uchida, Yasuo
Sato, Risa
Sasaki, Hayate
Nemoto, Shumpei
Terasaki, Tetsuya
Kusuhara, Hiroyuki
author_facet Ishiguro, Hiromu
Mizuno, Tadahaya
Uchida, Yasuo
Sato, Risa
Sasaki, Hayate
Nemoto, Shumpei
Terasaki, Tetsuya
Kusuhara, Hiroyuki
author_sort Ishiguro, Hiromu
collection PubMed
description Transcriptomic data of cultured cells treated with a chemical are widely recognized as useful numeric information that describes the effects of the chemical. This property is due to the high coverage and low arbitrariness of the transcriptomic data as profiles of chemicals. Considering the importance of posttranslational regulation, proteomic profiles could provide insights into the unrecognized aspects of the effects of chemicals. Therefore, this study aimed to address the question of how well the proteomic profiles obtained using data-independent acquisition (DIA) with the sequential window acquisition of all theoretical mass spectra, which can achieve comprehensive and arbitrariness-free protein quantification, can describe chemical effects. We demonstrated that the proteomic data obtained using DIA-MS exhibited favorable properties as profile data, such as being able to discriminate chemicals like the transcriptomic profiles. Furthermore, we revealed a new mode of action of a natural compound, harmine, through profile data analysis using the proteomic profile data. To our knowledge, this is the first study to investigate the properties of proteomic data obtained using DIA-MS as the profiles of chemicals. Our 54 (samples) × 2831 (proteins) data matrix would be an important source for further analyses to understand the effects of chemicals in a data-driven manner.
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spelling pubmed-100067302023-03-12 Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method Ishiguro, Hiromu Mizuno, Tadahaya Uchida, Yasuo Sato, Risa Sasaki, Hayate Nemoto, Shumpei Terasaki, Tetsuya Kusuhara, Hiroyuki NAR Genom Bioinform Standard Article Transcriptomic data of cultured cells treated with a chemical are widely recognized as useful numeric information that describes the effects of the chemical. This property is due to the high coverage and low arbitrariness of the transcriptomic data as profiles of chemicals. Considering the importance of posttranslational regulation, proteomic profiles could provide insights into the unrecognized aspects of the effects of chemicals. Therefore, this study aimed to address the question of how well the proteomic profiles obtained using data-independent acquisition (DIA) with the sequential window acquisition of all theoretical mass spectra, which can achieve comprehensive and arbitrariness-free protein quantification, can describe chemical effects. We demonstrated that the proteomic data obtained using DIA-MS exhibited favorable properties as profile data, such as being able to discriminate chemicals like the transcriptomic profiles. Furthermore, we revealed a new mode of action of a natural compound, harmine, through profile data analysis using the proteomic profile data. To our knowledge, this is the first study to investigate the properties of proteomic data obtained using DIA-MS as the profiles of chemicals. Our 54 (samples) × 2831 (proteins) data matrix would be an important source for further analyses to understand the effects of chemicals in a data-driven manner. Oxford University Press 2023-03-11 /pmc/articles/PMC10006730/ /pubmed/36915410 http://dx.doi.org/10.1093/nargab/lqad022 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Standard Article
Ishiguro, Hiromu
Mizuno, Tadahaya
Uchida, Yasuo
Sato, Risa
Sasaki, Hayate
Nemoto, Shumpei
Terasaki, Tetsuya
Kusuhara, Hiroyuki
Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
title Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
title_full Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
title_fullStr Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
title_full_unstemmed Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
title_short Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
title_sort characterization of proteome profile data of chemicals based on data-independent acquisition ms with swath method
topic Standard Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006730/
https://www.ncbi.nlm.nih.gov/pubmed/36915410
http://dx.doi.org/10.1093/nargab/lqad022
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